In [2]:
!pip install folium--0.5.0
!pip install folium==0.5.0

Collecting folium--0.5.0

  ERROR: Could not find a version that satisfies the requirement folium--0.5.0 (from versions: none)
ERROR: No matching distribution found for folium--0.5.0

Requirement already satisfied: folium==0.5.0 in c:\programdata\anaconda3\lib\site-packages (0.5.0)
Requirement already satisfied: six in c:\programdata\anaconda3\lib\site-packages (from folium==0.5.0) (1.12.0)
Requirement already satisfied: branca in c:\programdata\anaconda3\lib\site-packages (from folium==0.5.0) (0.4.1)
Requirement already satisfied: requests in c:\users\kkrezk\appdata\roaming\python\python37\site-packages (from folium==0.5.0) (2.23.0)
Requirement already satisfied: jinja2 in c:\users\kkrezk\appdata\roaming\python\python37\site-packages (from folium==0.5.0) (2.11.2)
Requirement already satisfied: certifi>=2017.4.17 in c:\programdata\anaconda3\lib\site-packages (from requests->folium==0.5.0) (2019.9.11)
Requirement already satisfied: urllib3!=1.25.0,!=1.25.1,<1.26,>=1.21.1 in c:\programdata\anaconda3\lib\site-packages (from requests->folium==0.5.0) (1.24.2)
Requirement already satisfied: chardet<4,>=3.0.2 in c:\programdata\anaconda3\lib\site-packages (from requests->folium==0.5.0) (3.0.4)
Requirement already satisfied: idna<3,>=2.5 in c:\programdata\anaconda3\lib\site-packages (from requests->folium==0.5.0) (2.8)
Requirement already satisfied: MarkupSafe>=0.23 in c:\programdata\anaconda3\lib\site-packages (from jinja2->folium==0.5.0) (1.1.1)
In [4]:
folium.__version__

---------------------------------------------------------------------------
NameError                                 Traceback (most recent call last)
<ipython-input-4-b597d2b812ff> in <module>
----> 1 folium.__version__

NameError: name 'folium' is not defined
In [7]:
import pandas as pd
import numpy as np
%matplotlib inline
import matplotlib.pyplot as plt
import matplotlib
matplotlib.style.use(['seaborn'])
import folium
import json

df_history = pd.read_csv('C:/Users/kkrezk/serie_historica_acumulados.csv',encoding = "ISO-8859-1")
df_history.rename(columns={'FECHA':'Date', 'CASOS':'Cases', 'Hospitalizados':'Hospitalized', 'UCI':'ICU', 'Fallecidos':'Deceased','Recuperados':'Recovered'}, inplace=True)
df_history.drop(df_history.tail(5).index,inplace=True)
df_history['CCAA'] = df_history['CCAA'].apply(lambda x: "{}{}".format('ES.', x))
df_history.tail()
Out[7]:
CCAA Date Cases PCR+ TestAc+ Hospitalized ICU Deceased Recovered
1230 ES.ML 24/4/2020 NaN 108.0 10.0 44.0 3.0 2.0 77.0
1231 ES.MC 24/4/2020 NaN 1468.0 288.0 625.0 105.0 126.0 842.0
1232 ES.NC 24/4/2020 NaN 4627.0 647.0 1937.0 129.0 429.0 1737.0
1233 ES.PV 24/4/2020 NaN 12366.0 1766.0 6375.0 525.0 1212.0 8941.0
1234 ES.RI 24/4/2020 NaN 3821.0 1125.0 1360.0 83.0 311.0 1999.0
In [8]:
final=pd.pivot_table(df_history, values=['Cases','PCR+','TestAc+','Hospitalized','ICU','Deceased','Recovered'], index='CCAA',
                     aggfunc={'Cases':max,'PCR+':max,'TestAc+':max,'Hospitalized':max,'ICU':max,'Deceased':max,'Recovered':max})


df_final = final.reset_index()
df_final
Out[8]:
CCAA Cases Deceased Hospitalized ICU PCR+ Recovered TestAc+
0 ES.AN 10426.0 1131.0 5715.0 717.0 11703.0 4295.0 1121.0
1 ES.AR 4338.0 709.0 2372.0 291.0 4922.0 1929.0 460.0
2 ES.AS 2096.0 239.0 1760.0 132.0 2238.0 716.0 308.0
3 ES.CB 1990.0 182.0 982.0 78.0 2071.0 1046.0 244.0
4 ES.CE 98.0 4.0 10.0 4.0 100.0 98.0 25.0
5 ES.CL 15293.0 1639.0 7555.0 511.0 15990.0 6033.0 2269.0
6 ES.CM 16349.0 2292.0 8385.0 559.0 15509.0 4876.0 3016.0
7 ES.CN 1975.0 130.0 878.0 171.0 2155.0 1036.0 0.0
8 ES.CT 38316.0 4498.0 24130.0 2576.0 46261.0 16753.0 1027.0
9 ES.EX 2762.0 416.0 1447.0 113.0 2718.0 1510.0 740.0
10 ES.GA 9196.0 388.0 2722.0 178.0 9116.0 1783.0 0.0
11 ES.IB 1668.0 174.0 1058.0 167.0 1847.0 1102.0 60.0
12 ES.MC 1520.0 126.0 625.0 105.0 1468.0 842.0 288.0
13 ES.MD 51993.0 7848.0 15227.0 1528.0 58819.0 34902.0 3691.0
14 ES.ML 104.0 2.0 44.0 3.0 108.0 77.0 10.0
15 ES.NC 4433.0 429.0 1937.0 129.0 4627.0 1737.0 647.0
16 ES.PV 12355.0 1212.0 6375.0 525.0 12366.0 8941.0 1899.0
17 ES.RI 3457.0 311.0 1360.0 83.0 3821.0 1999.0 1125.0
18 ES.VC 9615.0 1172.0 4978.0 653.0 10066.0 6033.0 1057.0
In [10]:
with open('C:/Users/kkrezk/shapefiles_ccaa_espana.geojson', 'r') as file:
     file_content = json.loads(file.read())
In [12]:
world_map = folium.Map(location=[40.4637, 0.5492], zoom_start=5.5)
world_geo = r'C:/Users/kkrezk/shapefiles_ccaa_espana.geojson'
world_map.choropleth(
    geo_data=world_geo,
    data=df_final,
    columns=['CCAA', 'Cases'],
    key_on='feature.properties.hasc_1',
    fill_color='YlOrRd', 
    fill_opacity=0.7, 
    line_opacity=0.2,
    legend_name='CAVID-19 cases'
)
world_map
Out[12]:
Make this Notebook Trusted to load map: File -> Trust Notebook
In [ ]: